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Predictive modeling leverages machine learning algorithms to predict missing values based on the relationship between other features. It is highly accurate and preserves the dataset’s integrity, which is crucial for data-driven analysis. Advanced techniques, like k-Nearest Neighbors or regression imputation, ensure minimal bias and better prediction accuracy compared to simpler methods. Why Other Options Are Wrong : A) Deleting rows reduces the dataset size, leading to loss of valuable information. B) Replacing with column mean ignores data variability and may distort outcomes. C) Leaving missing values untreated can affect the performance of analytical models. E) Adding a new column may highlight missing data but does not address the underlying issue.
Consider the following demand function of X for a commodity A
x= 10 + 0.10m/p
Money income (m) of X is Rs.120 and the price of A (p) is Rs...
The coefficient of regression of Y on X is byx = 1.2 , If A = (X-300)/4 and C = (Y-500)/6 find bCA
Which of the following statement is the objective(s) of setting up of Regional rural banks?
(i) development of agriculture, trade and other pr...
Which branch of economics deals with the study of the economic activities of individual units?
Which of the following is/are true at equilibrium in a perfect competition?
(1) MR = MC
(2) AC = MC = AR = MR
(3) MC is falling
The marginal cost curve is__________.
Which of the following statements is INCORRECT about the Finance Commission?
Which of the following statements are correct about trilemma in monetary policy
A. It is related to closed economy model.
B. It involves...
________ was an important growth strategy adopted by India prior to 1991.
Give below are two statements:
Statement - I: The terms of trade of a nation are defined as the ratio of the cost of its export commodity to th...